Bibliographic record
Abstract
Abstract Objective To assess the communication and interviewing skills of incoming residents and provide formative feedback to residents early in their training. Design New residents completed a 15-minute objective structured clinical examination (OSCE) assessing communication skills and a 12-question, self-administered content quiz at the start of their residency. Each resident was directly observed by a family physician in the OSCE and provided with 15 minutes of structured feedback, with an opportunity for questions and discussion. The entire process remained private and did not affect summative evaluations. Setting Family medicine residency training program at the University of Alberta in Edmonton. Participants First-year family medicine residents. Main outcome measures Residents’ scores on the OSCE and the content quiz; residents’ rating of the usefulness of the assessment and the likelihood it would lead to practice change. Results A total of 61 residents (93.8%) completed the skills assessment (50 Canadian graduates, 11 international graduates). The mean score for the content quiz was 20.6 out of a total possible score of 24. Resident scores ranged from 8 to 24. The mean score on the OSCE practice interview was 21.1 out of 30, with a range of 13 to 29. Learner feedback indicated that the skills assessment was useful (4.68 out of 6) and would lead to a change in practice (4.43 out of 6). Conclusion The introductory communication OSCE and quiz offer new residents an opportunity to gauge their baseline skill level, become aware of program expectations early in their training, and garner specific suggestions in a nonthreatening environment. This tailored approach helps orient residents while taking into account their previous experiences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".